Locating Particle Positions Through Gaussian Fitting of Circular Diffraction Spots in Images
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Accurate particle localization is achieved through Gaussian fitting techniques. Specifically, this method involves analyzing and processing approximately circular diffraction spots generated by particles in images to determine their precise coordinates. This approach provides enhanced precision for studying particle distribution characteristics, thereby establishing a robust foundation for advanced research and analysis.
Key implementation typically involves: - Preprocessing steps like background subtraction and noise reduction - Using 2D Gaussian fitting functions (e.g., MATLAB's lsqcurvefit or fit function) - Implementing peak detection algorithms to identify candidate particles - Calculating center coordinates through Gaussian parameters optimization The Gaussian model: f(x,y) = A*exp(-[(x-x₀)²/2σ_x² + (y-y₀)²/2σ_y²]) where (x₀,y₀) represents the particle center
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